Parse exif general encoded date (#137)

db/access/files.py

@@ -68,9 +68,6 @@ class ListFilesResults:
 class FilesDAO:
     """Data-access object for files."""
 
-    # Format in which Dates are currently stored in exif table.
-    _EXIF_DATE_FORMAT = " UTC %Y-%m-%d 00"
-
     # Label for related entities count (matches, scenes, etc.)
     _LABEL_COUNT = "hit_count"
     _countable_match = aliased(Matches)
@@ -197,11 +194,11 @@ def _filter_date(req: ListFilesRequest, query):
         """Filter by creation date."""
         if req.date_from is not None:
             query = query.filter(
-                Files.exif.has(Exif.General_Encoded_Date >= req.date_from.strftime(FilesDAO._EXIF_DATE_FORMAT)))
+                Files.exif.has(Exif.General_Encoded_Date >= req.date_from))
 
         if req.date_to is not None:
             query = query.filter(
-                Files.exif.has(Exif.General_Encoded_Date <= req.date_to.strftime(FilesDAO._EXIF_DATE_FORMAT)))
+                Files.exif.has(Exif.General_Encoded_Date <= req.date_to))
 
         return query
 

db/schema.py

@@ -1,9 +1,9 @@
 import datetime
 
 from sqlalchemy import Column, String, Integer, LargeBinary, Boolean, \
-    Float, JSON, ForeignKey, UniqueConstraint, DateTime,PrimaryKeyConstraint,event
+    Float, JSON, ForeignKey, UniqueConstraint, DateTime, event
 from sqlalchemy.ext.declarative import declarative_base
-from sqlalchemy.orm import relationship,backref,object_session
+from sqlalchemy.orm import relationship, object_session
 
 Base = declarative_base()
 
@@ -19,7 +19,7 @@ class Files(Base):
     signature = relationship("Signature", uselist=False, back_populates="file")
     meta = relationship("VideoMetadata", uselist=False, back_populates="file")
     scenes = relationship("Scene", back_populates="file")
-    templatematches = relationship("Templatematches", back_populates="file",cascade='all, delete-orphan')
+    templatematches = relationship("Templatematches", back_populates="file", cascade='all, delete-orphan')
     exif = relationship("Exif", uselist=False, back_populates="file")
 
     # TODO: find a way to merge these two relationships
@@ -74,16 +74,17 @@ class Scene(Base):
 class Templatematches(Base):
     __tablename__ = 'templatematches'
     # __table_args__ = (UniqueConstraint('file_id', 'template_name'),)
-    id = Column(Integer,autoincrement=True,primary_key=True)
+    id = Column(Integer, autoincrement=True, primary_key=True)
     file_id = Column(Integer, ForeignKey('files.id'), nullable=True)
-    file = relationship("Files",back_populates='templatematches')
+    file = relationship("Files", back_populates='templatematches')
     template_name = Column(String)
     distance = Column(Float)
     closest_match = Column(Float)
     closest_match_time = Column(String)
 
-@event.listens_for(Files.templatematches,"remove")
-def rem(state,item,initiator):
+
+@event.listens_for(Files.templatematches, "remove")
+def rem(state, item, initiator):
     sess = object_session(item)
 
     # ensure we have a session
@@ -98,8 +99,6 @@ def rem(state,item,initiator):
     sess.flush([item])
 
 
-
-
 class Matches(Base):
     __tablename__ = 'matches'
     __table_args__ = (UniqueConstraint('query_video_file_id', 'match_video_file_id', name='_matches_uc'),)
@@ -130,9 +129,9 @@ class Exif(Base):
     General_OverallBitRate = Column(Float)
     General_FrameRate = Column(Float)
     General_FrameCount = Column(Float)
-    General_Encoded_Date = Column(String)
-    General_File_Modified_Date = Column(String)
-    General_File_Modified_Date_Local = Column(String)
+    General_Encoded_Date = Column(DateTime)
+    General_File_Modified_Date = Column(DateTime)
+    General_File_Modified_Date_Local = Column(DateTime)
     General_Tagged_Date = Column(String)
     Video_Format = Column(String)
     Video_BitRate = Column(Float)
@@ -146,6 +145,6 @@ class Exif(Base):
     Audio_BitRate = Column(Float)
     Audio_Channels = Column(Float)
     Audio_Duration = Column(Float)
-    Audio_Encoded_Date = Column(String)
-    Audio_Tagged_Date = Column(String)
+    Audio_Encoded_Date = Column(DateTime)
+    Audio_Tagged_Date = Column(DateTime)
     Json_full_exif = Column(JSON)

server/tests/server/test_api.py

@@ -119,7 +119,7 @@ def make_file(prefix="", length=42, ext="flv", audio=True, date=datetime.date(20
     sha256 = f"hash-of-{path}"
     return Files(file_path=path, sha256=sha256,
                  exif=Exif(General_FileExtension=ext, Audio_Duration=float(audio),
-                           General_Encoded_Date=backend_date(date)),
+                           General_Encoded_Date=date),
                  meta=VideoMetadata(video_length=length),
                  scenes=[Scene(start_time=start, duration=duration) for start, duration in scenes])
 
@@ -132,11 +132,6 @@ def make_files(count, prefix="", length=42, ext="flv", audio=True, date=datetime
     ]
 
 
-def backend_date(date):
-    """Convert date to format utilized in the backend."""
-    return date.strftime(" UTC %Y-%m-%d 00")
-
-
 def param_date(date):
     """Convert date to REST API parameter format."""
     return date.strftime("%Y-%m-%d")

web/src/server-api/Server/Transform.js

@@ -1,5 +1,4 @@
 import { randomObjects } from "../MockServer/fake-data/objects";
-import { parse as parseDate } from "date-fns";
 
 /**
  * Data-transfer object and internal data format may evolve independently, the
@@ -48,7 +47,7 @@ export default class Transform {
     if (value == null) {
       return null;
     }
-    return parseDate(value, "'UTC' yyyy-MM-dd HH", new Date());
+    return new Date(value * 1000);
   }
 
   fileMetadata(data) {

winnow/storage/db_result_storage.py

@@ -37,7 +37,6 @@ def wrapped(*args, **kwargs):
         logger.debug(f"{func.__name__}(...) took {end - start:5.3} seconds")
         return result
 
-    wrapped.__name__ = func.__name__
     return wrapped
 
 

winnow/utils/metadata_extraction.py

@@ -1,12 +1,15 @@
 import logging
+import os
 import shlex
 import subprocess
 from collections import defaultdict
-import pandas as pd
-from pandas.io.json import json_normalize
+from datetime import datetime, timezone
+
 import cv2
-import os
 import numpy as np
+import pandas as pd
+from pandas.io.json import json_normalize
+
 logger = logging.getLogger(__name__)
 
 
@@ -35,9 +38,9 @@ def process_media_info(info):
         if ':' not in line:
             section = line
         else:
-            key, val, *_ = line.split(':')
+            key, val = line.split(':', maxsplit=1)
             section, key = section.strip(), key.strip()
-            metadata[section][key] = val
+            metadata[section][key] = val.lstrip()
     return dict(metadata)
 
 
@@ -172,33 +175,69 @@ def convert_to_df(video_metadata):
        'Audio_Channels',
        'Audio_Duration']
 
+# Date column of interest
+DCI = [
+        'General_Encoded_Date',
+        'General_File_Modified_Date',
+        'General_File_Modified_Date_Local',
+        'Audio_Encoded_Date',
+        'Audio_Tagged_Date']
+
+# Exif date format
+_EXIF_DATE_FORMAT = "%Y-%m-%d %H:%M:%S"
+
+
+def parse_timezone(str_value):
+    if str_value.startswith("UTC"):
+        return timezone.utc, str_value[3:].lstrip()
+    return None, str_value
 
-def parse_and_filter_metadata_df(metadata_df):
 
-    GCI = [
-                                x for x in CI
-                                if x in metadata_df.columns
-                                ]
-    GNI = [
-                                        x for x in NCI
-                                        if x in metadata_df.columns
-                                        ]
-    GSI = [
-                                x for x in GCI
-                                if x not in GNI
-                                    ]
-
-    filtered = metadata_df.loc[:, GCI]
+def parse_date(str_value: str):
+    try:
+        time_zone, str_value = parse_timezone(str_value)
+        return datetime.strptime(str_value, _EXIF_DATE_FORMAT).replace(tzinfo=time_zone)
+    except ValueError:
+        logger.exception("Cannot parse exif date")
+
+
+def parse_and_filter_metadata_df(metadata_df):
+    all_columns = [
+        column_name for column_name in CI
+        if column_name in metadata_df.columns
+    ]
+    numeric_columns = [
+        column_name for column_name in NCI
+        if column_name in metadata_df.columns
+    ]
+    date_columns = [
+        column_name for column_name in DCI
+        if column_name in metadata_df.columns
+    ]
+    string_columns = [
+        column_name for column_name in all_columns
+        if column_name not in numeric_columns and column_name not in date_columns
+    ]
+
+    filtered = metadata_df.loc[:, all_columns]
 
     # Parsing numerical fields
-    filtered.loc[:, GNI] = (filtered.loc[:, GNI]
-                            .apply(lambda x: pd.to_numeric(x, errors='coerce'))
-                            )
-
-    filtered.loc[:, GSI] = (filtered
-                            .loc[:, GSI]
-                            .fillna('N/A')
-                            .apply(lambda x: x.str.strip())
-                            )
+    filtered.loc[:, numeric_columns] = (
+        filtered.loc[:, numeric_columns]
+            .apply(lambda x: pd.to_numeric(x, errors='coerce'))
+    )
+
+    # Parsing date fields
+    filtered.loc[:, date_columns] = (
+        filtered.loc[:, date_columns]
+            .apply(lambda column: column.apply(parse_date))
+    )
+
+    filtered.loc[:, string_columns] = (
+        filtered
+            .loc[:, string_columns]
+            .fillna('N/A')
+            .apply(lambda x: x.str.strip())
+    )
 
     return filtered